Dlib is a modern C++ toolkit containing machine learning algorithms and
tools for creating complex software in C++ to solve real world problems.
It is used in both industry and academia in a wide range of domains
including robotics, embedded devices, mobile phones, and large high
performance computing environments. Dlib's open source licensing
allows you to use it in any application, free of charge.

To follow or participate in the development of dlib subscribe to dlib on github.
Also be sure to read the how to contribute page if you intend to
submit code to the project.

Major Features

Documentation

Unlike a lot of open source projects, this one provides complete and precise
documentation for every class and function. There are also debugging modes that check the
documented preconditions for functions. When this is enabled it will catch the vast majority of
bugs caused by calling functions incorrectly or using objects in an incorrect manner.

Lots of example programs are provided

I consider the documentation to be the most important part of the library. So if you find anything
that isn't documented, isn't clear, or has out of date documentation, tell me and I will fix it.

High Quality Portable Code

Good unit test coverage. The ratio of unit test lines of code to library lines of
code is about 1 to 4.

The library is tested regularly on MS Windows, Linux, and Mac OS X systems. However, it should
work on any POSIX system and has been used on Solaris, HPUX, and the BSDs.

No other packages are required to use the library. Only APIs that are
provided by an out of the box OS are needed.

There is no installation or configure step needed before you can use the library. See the
How to compile page for details.

All operating system specific code is isolated inside the OS abstraction layers which are
kept as small as possible. The rest of the library is either layered on top of the OS
abstraction layers or is pure ISO standard C++.